SOTAVerified

Reinforcement Learning (RL)

Reinforcement Learning (RL) involves training an agent to take actions in an environment to maximize a cumulative reward signal. The agent interacts with the environment and learns by receiving feedback in the form of rewards or punishments for its actions. The goal of reinforcement learning is to find the optimal policy or decision-making strategy that maximizes the long-term reward.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3376–3400 of 15113 papers

TitleStatusHype
Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces—0
Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors—0
SAMG: State-Action-Aware Offline-to-Online Reinforcement Learning with Offline Model Guidance—0
PointPatchRL -- Masked Reconstruction Improves Reinforcement Learning on Point Clouds—0
Learn 2 Rage: Experiencing The Emotional Roller Coaster That Is Reinforcement Learning—0
Primal-Dual Spectral Representation for Off-policy Evaluation—0
Optimizing Load Scheduling in Power Grids Using Reinforcement Learning and Markov Decision Processes—0
Dynamic Spectrum Access for Ambient Backscatter Communication-assisted D2D Systems with Quantum Reinforcement Learning—0
Learning Versatile Skills with Curriculum MaskingCode0
The Hive Mind is a Single Reinforcement Learning Agent—0
Process Supervision-Guided Policy Optimization for Code Generation—0
Meta Stackelberg Game: Robust Federated Learning against Adaptive and Mixed Poisoning Attacks—0
Survival of the Fittest: Evolutionary Adaptation of Policies for Environmental Shifts—0
DROP: Distributional and Regular Optimism and Pessimism for Reinforcement Learning—0
Exploring RL-based LLM Training for Formal Language Tasks with Programmed RewardsCode0
Episodic Future Thinking Mechanism for Multi-agent Reinforcement Learning—0
DyPNIPP: Predicting Environment Dynamics for RL-based Robust Informative Path Planning—0
Multi-Modal Transformer and Reinforcement Learning-based Beam Management—0
Curriculum Reinforcement Learning for Complex Reward Functions—0
Benchmarking Smoothness and Reducing High-Frequency Oscillations in Continuous Control Policies—0
Offline reinforcement learning for job-shop scheduling problems—0
Reinforcement Learning for Dynamic Memory AllocationCode0
Training Language Models to Critique With Multi-agent Feedback—0
MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning—0
Augmented Lagrangian-Based Safe Reinforcement Learning Approach for Distribution System Volt/VAR Control—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1PPGMean Normalized Performance0.76—Unverified
2PPOMean Normalized Performance0.58—Unverified